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Title: On Pleiotropy and Evolutionary Dynamics in the Buddying Yeast Saccharomyces cerevisiae
Abstract: Evolving populations optimize over complex fitness landscapes in a way that allows for biological innovations to arise. Understanding of this process requires data on the specific statistical and dynamical aspects that are relevant in natural biological systems, as it is not clear that they can be inferred from first principles. In particular, one property that is crucial to the way populations evolve in a complex environment is the distribution of pleiotropic effects of novel mutations, that is, how it is that mutations affect different phenotypes or fitness in different environments. In this dissertation, I present three different research projects where we use data to directly investigate aspects of the evolutionary dynamics and statistics of the pleiotropic genetic basis of phenotypes in the bud- dying yeast Saccharomyces cerevisiae. Chapter 2 makes use of genetic engineering and robotics to substantially increase statistical power in yeast quantitative trait loci studies, which we use to uncover highly polygenic, pleiotropic, and epistatic genetic architectures of complex traits. Chapter 3 employs temporal metagenomic sequencing of fermenting yeast sourced from bioethanol refineries to explore the evolutionary dynamics in very large and genetically diverse microbial populations, revealing a complex picture that calls for eco-evolutionary explanations. Chapter 4 adopts a recently- developed high-resolution lineage tracking technique to investigate the adaptation of two asexual budding yeast populations subjected to fluctuating environments, with evolutionary outcomes largely depending on the pleiotropic effects of novel mutations and the environmental regime.
Committee: Michael Desai (Advisor), Robin Hopkins, Andrew Murray (MCB), John Wakeley